Singular value decomposition
Singular value decomposition factors a matrix into orthogonal directions and nonnegative singular values. Truncated SVD supplies a best low-rank approximation under common matrix norms and informs compression techniques.
A=U\Sigma V^T
Overview. Singular value decomposition factors a matrix into orthogonal directions and nonnegative singular values.
Context. Truncated SVD supplies a best low-rank approximation under common matrix norms and informs compression techniques.
Claims and evidence
Claim ledger, 2Singular value decomposition factors a matrix into orthogonal directions and nonnegative singular values.
Truncated SVD supplies a best low-rank approximation under common matrix norms and informs compression techniques.